class_docstr: Interface for implementing a Trial Scheduler class.
  
  Note to Tune developers: If a new scheduler is added, please update
  `air/_internal/usage.py`.
docstr: Called on each intermediate result returned by a trial.
  
  At this point, the trial scheduler can make a decision by returning
  one of CONTINUE, PAUSE, and STOP. This will only be called when the
  trial is in the RUNNING state.
docstr_tok: ["Called","on","each","intermediate","result","returned","by","a","trial",".","At","this","point",",","the","trial","scheduler","can","make","a","decision","by","returning","one","of","CONTINUE",",","PAUSE",",","and","STOP",".","This","will","only","be","called","when","the","trial","is","in","the","RUNNING","state","."]
code: def on_trial_result(
      self,
      tune_controller: "TuneController",
      trial: Trial,
      result: Dict,
  ) -> str:
      """Called on each intermediate result returned by a trial.
  
      At this point, the trial scheduler can make a decision by returning
      one of CONTINUE, PAUSE, and STOP. This will only be called when the
      trial is in the RUNNING state."""
  
      raise NotImplementedError
  
imports: from typing import Dict, Optional, TYPE_CHECKING
  from ray.air._internal.usage import tag_scheduler
  from ray.tune.result import DEFAULT_METRIC
  from ray.tune.experiment import Trial
  from ray.util.annotations import DeveloperAPI, PublicAPI
label_desc: Use image node_id 7 for calling the TrialScheduler obj's underlying member method code with example usage: obj.on_trial_result(tune_controller, trial, result) without return types